Demonstrate the ratio estimation in sampling survey
This function demonstrates the advantage of ratio estimation when further information (ratio) about x and y is available.
sample.ratio(X = runif(50, 0, 5), R = 1, Y = R * X + rnorm(X), size = length(X)/2, p.col = c("blue", "red"), p.cex = c(1, 3), p.pch = c(20, 21), m.col = c("black", "gray"), legend.loc = "topleft", ...)
X |
the X variable (ancillary) |
R |
the population ratio Y/X |
Y |
the Y variable (whose mean we what to estimate) |
size |
sample size |
p.col, p.cex, p.pch |
point colors, magnification and symbols for the population and sample respectively |
m.col |
color for the horizontal line to denote the sample mean of Y |
legend.loc |
legend location: topleft, topright, bottomleft,
bottomright, ... (see |
... |
other arguments passed to |
From this demonstration we can clearly see that the ratio estimation is generally better than the simple sample average when the ratio R really exists, otherwise ratio estimation may not help.
A list containing
X |
X population |
Y |
Y population |
R |
population ratio |
r |
ratio calculated from samples |
Ybar |
population mean of Y |
ybar.simple |
simple sample mean of Y |
ybar.ratio |
sample mean of Y via ratio estimation |
Yihui Xie
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